For over six decades, the field of automated planning has been at the heart of AI, empowering intelligent systems to reason, act, and achieve goals in complex, dynamic environments. From robotics and logistics to space exploration, planning research has fueled autonomous decision-making in real-world applications.

Today, as large language models redefine what’s possible in AI, the principles and methodologies of planning are more vital than ever. The planning community brings decades of experience in designing, benchmarking, and interpreting intelligent behavior; expertise that can accelerate the development of powerful, trustworthy, and general-purpose LLM-based agents.

Participants will gain a clear understanding of what planning truly entails, what has been learned (and sometimes forgotten) in the shift toward LLM-based approaches, and how foundational insights from the planning community can inform the creation of stronger, more reliable, and more scalable LLM-powered planners.